TY - GEN
T1 - Implicit constraints for qualitative spatial and temporal reasoning
AU - Renz, Jochen
PY - 2012
Y1 - 2012
N2 - Qualitative information about spatial or temporal entities is represented by specifying qualitative relations between these entities. It is then possible to apply qualitative reasoning methods for tasks such as checking consistency of the given information, deriving previously unknown information or answering queries. Depending on the kind of information that is represented, qualitative reasoning methods might lead to incorrect results, and it is a topic of ongoing research efforts to determine when and why this occurs. In this paper we present two possible explanations for this behaviour: (1) the existence of implicit entities that we do not explicitly represent; (2) the existence of implicit constraints that have to be satisfied, but which are not explicitly represented. We show that both of these can lead to undetected inconsistencies. By making these implicit entities and constraints explicit, and by including them in the qualitative representation, we are able to solve problems that could not be solved qualitatively before. We present different examples of implicit entities and implicit constraints and an algorithm for solving them.
AB - Qualitative information about spatial or temporal entities is represented by specifying qualitative relations between these entities. It is then possible to apply qualitative reasoning methods for tasks such as checking consistency of the given information, deriving previously unknown information or answering queries. Depending on the kind of information that is represented, qualitative reasoning methods might lead to incorrect results, and it is a topic of ongoing research efforts to determine when and why this occurs. In this paper we present two possible explanations for this behaviour: (1) the existence of implicit entities that we do not explicitly represent; (2) the existence of implicit constraints that have to be satisfied, but which are not explicitly represented. We show that both of these can lead to undetected inconsistencies. By making these implicit entities and constraints explicit, and by including them in the qualitative representation, we are able to solve problems that could not be solved qualitatively before. We present different examples of implicit entities and implicit constraints and an algorithm for solving them.
UR - http://www.scopus.com/inward/record.url?scp=84893387258&partnerID=8YFLogxK
M3 - Conference contribution
SN - 9781577355601
T3 - Proceedings of the International Conference on Knowledge Representation and Reasoning
SP - 509
EP - 518
BT - 13th International Conference on the Principles of Knowledge Representation and Reasoning, KR 2012
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th International Conference on the Principles of Knowledge Representation and Reasoning, KR 2012
Y2 - 10 June 2012 through 14 June 2012
ER -